CONTEXT: Estimating life expectancy is challenging in advanced dementia. OBJECTIVES: To create a risk score to estimate survival in nursing home (NH) residents with advanced dementia. METHODS: This was a retrospective cohort study performed in the setting of all licensed U.S. NHs. Residents with advanced dementia living in U.S. NHs in 2002 were identified using Minimum Data Set (MDS) assessments. Mortality data from Medicare files were used to determine 12-month survival. Independent variables were selected from the MDS. Cox proportional hazards regression was used to model survival. The accuracy of the final model was assessed using the area under the receiver operating characteristic curve (AUROC). To develop a risk score, points were assigned to variables in the final model based on parameter estimates. Residents meeting hospice eligibility guidelines for dementia, based on MDS data, were identified. The AUROC assessed the accuracy of hospice guidelines to predict six-month survival. RESULTS: Over 12 months, 40.6% of residents with advanced dementia (n=22,405) died. Twelve variables best predicted survival: length of stay, age, male, dyspnea, pressure ulcers, total functional dependence, bedfast, insufficient intake, bowel incontinence, body mass index, weight loss, and congestive heart failure. The AUROC for the final model was 0.68. The risk score ranged from 1 to 32.5 points (higher scores indicate worse survival). Only 15.9% of residents met hospice eligibility guidelines for which the AUROC predicting six-month survival was 0.53. CONCLUSION: A mortality risk score derived from MDS data predicted six-month survival in advanced dementia with moderate accuracy. The predictive ability of hospice guidelines, simulated with MDS data, was poor.
CONTEXT: Estimating life expectancy is challenging in advanced dementia. OBJECTIVES: To create a risk score to estimate survival in nursing home (NH) residents with advanced dementia. METHODS: This was a retrospective cohort study performed in the setting of all licensed U.S. NHs. Residents with advanced dementia living in U.S. NHs in 2002 were identified using Minimum Data Set (MDS) assessments. Mortality data from Medicare files were used to determine 12-month survival. Independent variables were selected from the MDS. Cox proportional hazards regression was used to model survival. The accuracy of the final model was assessed using the area under the receiver operating characteristic curve (AUROC). To develop a risk score, points were assigned to variables in the final model based on parameter estimates. Residents meeting hospice eligibility guidelines for dementia, based on MDS data, were identified. The AUROC assessed the accuracy of hospice guidelines to predict six-month survival. RESULTS: Over 12 months, 40.6% of residents with advanced dementia (n=22,405) died. Twelve variables best predicted survival: length of stay, age, male, dyspnea, pressure ulcers, total functional dependence, bedfast, insufficient intake, bowel incontinence, body mass index, weight loss, and congestive heart failure. The AUROC for the final model was 0.68. The risk score ranged from 1 to 32.5 points (higher scores indicate worse survival). Only 15.9% of residents met hospice eligibility guidelines for which the AUROC predicting six-month survival was 0.53. CONCLUSION: A mortality risk score derived from MDS data predicted six-month survival in advanced dementia with moderate accuracy. The predictive ability of hospice guidelines, simulated with MDS data, was poor.
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